🤗 Kernels: Major Updates

Custom Kernels for All from Codex and Claude

Introducing @huggingface/kernels: 200+ WebGPU Kernels for Local AI

From Zero to GPU: A Guide to Building and Scaling Production-Ready CUDA Kernels

How Much of a Real Workload Can LLM-Generated GPU Kernels Actually Reach?

arXiv:2609.21058v1 Announce Type: cross Abstract: Language models can now write GPU kernels that outperform PyTorch. We evaluate five model configurations on KernelBench level 1 and find that a front...

Easily Build and Share ROCm Kernels with Hugging Face

What Do They Fix? LLM-Aided Categorization of Security Patches for Critical Memory Bugs

The paper introduces DUALLM, a dual-method pipeline that uses a Large Language Model and a fine‑tuned small language model to classify Linux kernel security patches with high precision. By analyzing commit titles, messages, diffs, and code context, DUALLM achieves 87.4% accuracy and an F1‑score of 0.875, outperforming existing methods. It successfully identified 111 recent patches addressing out‑of‑bounds or use‑after‑free vulnerabilities, with 90 confirmed true positives and proof‑of‑concept exploits demonstrating the validity of the classifications.